Neil Urquhart
Neil Urquhart

Dr Neil Urquhart

Lecturer

Biography

Dr Neil Urquhart is a lecturer within the School of Computing. After studying computing as an undergraduate he worked as a software developer and systems administrator in the printing and packaging sector.

He returned to academia and completed a PhD in 2002 which examined the use of nature inspired techniques and software agents to construct and optimise delivery networks.

Since 2002 he has worked as a lecturer within the School Of Computing at Edinburgh Napier where he is currently the programme leader for Computing Science.

Research Areas

News

Events

Esteem

Conference Organising Activity

  • Genetic and Evolutionary Computation Conference (GECCO) 2010
  • Neil Urquhart to chair Meta-Heuristics stream at YOR19
  • Co-Chair EvoStim 2011
  • Meta-heuristics stream chair for YOR17.
  • Two CAVES members have papers accepted at EvoSTAR Conference to be held in Copenhagen in April
  • Dr Neil Urquhart and Kevin Sim are to chair the second edition of EvoINDUSTRY at EvoStar 2014 in Baeza Spain.
  • Edinburgh Napier Staff Conference 2013 (member of conference planning group)

 

Editorial Activity

  • New book on automated scheduling and planning, being published by Springer due for release late 2013.

 

Media Activity

  • Optimisation@IIDI featured on LogisticsManager.Com

 

Date


79 results

Routing using evolutionary agents and proactive transitions.

Book
Urquhart, N. B., Ross, P., Paechter, B., & Chisholm, K. (2002)
Routing using evolutionary agents and proactive transitions. In Applications of Evolutionary Computing, 696-705. Springer-Verlag
The authors have previously introduced the concept of building a delivery network using an agent-based system. The delivery networks are built in response to a real-world prob...

Solving a real world routing problem using multiple evolutionary algorithms.

Conference Proceeding
Urquhart, N. B., Ross, P., Paechter, B., & Chisholm, K. (2002)
Solving a real world routing problem using multiple evolutionary algorithms. In Parallel Problem Solving from Nature — PPSN VII. , (871-880). https://doi.org/10.1007/3-540-45712-7_84
This paper investigates the solving of a real world routing problem using evolutionary algorithms embedded within a Multi-agent system (MAS). An architecture for the MAS is pr...

Solving a real world routing problem using evolutionary agents.

Conference Proceeding
Urquhart, N. B., Ross, P., Paechter, B. & Chisholm, K. (2002)
Solving a real world routing problem using evolutionary agents. ISBN 3540441395
This paper investigates the solving of a real world routing problem using evolutionary algorithms embedded within a Multi-agent system (MAS). An architecture for the MAS is pr...

Improving street based routing using building block mutations.

Conference Proceeding
Urquhart, N. B., Ross, P., Paechter, B., & Chisholm, K. (2002)
Improving street based routing using building block mutations. In J. Gottlieb, E. Hart, & S. Cagnoni (Eds.), Applications of Evolutionary Computing: EvoWorkshops 2002: EvoCOP, EvoIASP, EvoSTIM/EvoPLAN Kinsale, Ireland, April 3–4, 2002 Proceedings. , (189-202). https://doi.org/10.1007/3-540-46004-7_33
Street based routing (SBR) is a real-world inspired routing problem that builds routes within an urban area for mail deliveries. The authors have previously attempted to solve...

Street-based routing using an evolutionary algorithm

Conference Proceeding
Urquhart, N. B., Paechter, B., & Chisholm, K. (2001)
Street-based routing using an evolutionary algorithm. In E. J. W. Boers, J. Gottlieb, P. L. Lanzi, R. E. Smith, S. Cagnoni, E. Hart, …H. Tijink (Eds.), Applications of Evolutionary Computing: EvoWorkshops 2001: EvoCOP, EvoFlight, EvoIASP, EvoLearn, and EvoSTIM, Proceedings. , (495-504). https://doi.org/10.1007/3-540-45365-2_51
Much research has been carried out into solving routing problems using both Evolutionary Techniques and other methods. In this paper the authors investigate the usage of an Ev...

Optimising an evolutionary algorithm for scheduling

Conference Proceeding
Urquhart, N. B., Chisholm, K., & Paechter, B. (2000)
Optimising an evolutionary algorithm for scheduling. In S. Cagnoni, R. Poli, G. D. Smith, D. Corne, M. Oates, E. Hart, …T. C. Fogarty (Eds.), Real-World Applications of Evolutionary Computing: EvoWorkshops 2000: EvoIASP, EvoSCONDI, EvoTel, EvoSTIM, EvoRob, and EvoFlight, Proceedings. , (307-318). https://doi.org/10.1007/3-540-45561-2_30
This paper examines two techniques for setting the parameters of an evolutionary Algorithm (EA). The example EA used for test purposes undertakes a simple scheduling problem. ...

Optimising an Evolutionary Algorithm for Scheduling

Conference Proceeding
Urquhart, N., Chisholm, K., & Paechter, B. (2000)
Optimising an Evolutionary Algorithm for Scheduling. In Real-World Applications of Evolutionary Computing: EvoWorkshops 2000. , (307-318
This paper examines two techniques for setting the parameters of an evolutionary Algorithm (EA). The example EA used for test purposes undertakes a simple scheduling problem. ...

An application of CoSMoS design methods to pedestrian simulation.

Conference Proceeding
Clayton, S. & Urquhart, N. B. (2008)
An application of CoSMoS design methods to pedestrian simulation. In Welch, P. H., Roebbers, H., Broenink, J. F., Barnes, F. R. M., Ritson, C. G., Sampson, A. T., …Vinter, B. (Eds.). Communicating Process Architectures 2009 WoTUG-32doi:10.3233/978-1-60750-065-0-197. ISBN 978-1-60750-065-0
In this paper, we discuss the implementation of a simple pedestrian simulation that uses a multi agent based design pattern developed by the CoSMoS research group. Given the n...

Agent motion planning with GAs enhanced by memory models.

Journal Article
Bot, M., Urquhart, N. B. & Chisholm, K. (2000)
Agent motion planning with GAs enhanced by memory models. Genetic and Evolutionary Computation Conference. , 227-234
The Tartarus problem may be considered a benchmark problem in the field of robotics. A robotic agent is required to move a number of blocks to the edge of an environment. The ...

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